Several OOD detection methods have been proposed to predict an ID probability explicitly.
Hendrycks and Gimpel were one of the first to address this problem [1]}.
They used the maximum value of the softmax prediction as ID probability (Max. Softmax).
In their work, they motivate this choice by observing that the highest prediction is lower for OOD samples than ID samples.
As the softmax is commonly used for single-label classification problems, they extended the method to multi-label classification problems by taking the maximum prediction of the sigmoid (Max. Prediction) [2]}.
Alternatively, they propose to use the maximum of the underlying logits, the input to the sigmoid layer (Max. Logit).
Wang et al. use the label-wise energy function [3]} instead of the sigmoid to transform the output of the model to an ID probability score (Max. Energy) [4]}.
